Data processing method, computing device, storage medium and computer program product

Abstract

The embodiment of the invention relates to the technical field of data processing, in particular to a data processing method, computing equipment, a storage medium and a computer program product.The data processing method comprises the steps that in response to a file processing event of a target item, a target file of the target item is determined; performing data extraction on the target file to obtain target project data recorded in the target file; and according to the target project data, generating a file tag corresponding to the target file by utilizing a preset generation rule, so as to retrieve the target project according to the file tag.

Description

Technical Field

[0001] The embodiments of this specification relate to the field of data processing technology, and in particular, to data processing methods, computing devices, storage media, and computer program products. Background Art

[0002] In the current era of information explosion, how to achieve the management and collaboration of complex and diverse information has become a challenge. Usually, different types of information are widely scattered across multiple tools and platforms and managed through different platforms. For example, file management platforms can usually be used to store project files, and different types of communication tools can be used to store different information such as communication records and emails. When retrieving information, it is usually necessary to search on different tools or platforms, resulting in lengthy and cumbersome information retrieval and information integration processes, low information processing efficiency, and resource occupation of computing devices. Therefore, an effective technical solution is urgently needed to solve the above problems. Summary of the invention

[0003] In view of this, the embodiments of this specification provide two data processing methods. One or more embodiments of this specification also involve two data processing devices, a computing device, a computer-readable storage medium and a computer program product to solve the technical defects existing in the prior art.

[0004] According to a first aspect of an embodiment of this specification, a data processing method is provided, which is applied to a project management intelligent platform, including: In response to a file processing event of a target project, determining a target file of the target project; Extracting data from the target file to obtain target project data recorded in the target file; According to the target project data, a file tag corresponding to the target file is generated using a preset generation rule, so as to retrieve the target project according to the file tag.

[0005] According to a second aspect of the embodiments of this specification, there is provided a data processing device, which is applied to a project management intelligent platform, including: A determination module, configured to determine a target file of the target project in response to a file processing event of the target project; An extraction module is configured to extract data from the target file to obtain target project data recorded in the target file; The generation module is configured to generate a file tag corresponding to the target file according to the target project data and using a preset generation rule, so as to retrieve the target project according to the file tag.

[0006] According to a third aspect of an embodiment of this specification, a data processing method is provided, including: Receiving a file search instruction for a target project from a target user, wherein the file search instruction carries a search keyword; Determine the retrieval file corresponding to the file retrieval instruction according to the retrieval keyword and the file tags of the multiple target files in the target project, wherein the file tags of the multiple target files in the target project are determined according to the method provided in the first aspect of the embodiment of this specification; The retrieved file is displayed to the target user.

[0007] According to a fourth aspect of an embodiment of this specification, there is provided a data processing device, including: A receiving module is configured to receive a file search instruction from a target user for a target project, wherein the file search instruction carries a search keyword; a determination module configured to determine the retrieval file corresponding to the file retrieval instruction according to the retrieval keyword and the file tags of the multiple target files in the target project, wherein the file tags of the multiple target files in the target project are determined according to the method provided in the first aspect of the embodiment of this specification; A display module is configured to display the retrieved file to the target user.

[0008] According to a fifth aspect of an embodiment of this specification, a computing device is provided, including: Memory and processor; The memory is used to store computer programs / instructions, and the processor is used to execute the computer programs / instructions. When the computer programs / instructions are executed by the processor, the steps of the above method are implemented.

[0009] According to a sixth aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores a computer program / instruction, and the steps of the above method are implemented when the computer program / instruction is executed by a processor.

[0010] According to a seventh aspect of the embodiments of this specification, a computer program product is provided, comprising a computer program / instruction, which implements the steps of the above method when executed by a processor.

[0011] An embodiment of the present specification provides a data processing method, which is applied to a project management intelligent platform, including: determining a target file of the target project in response to a file processing event of the target project; extracting data from the target file to obtain target project data recorded in the target file; and generating a file tag corresponding to the target file based on the target project data using preset generation rules, so as to retrieve the target project based on the file tag.

[0012] In the above method, the project intelligent management platform is used to uniformly manage the target files of the target project. Specifically, data can be extracted from the target file to obtain the target project data recorded in the target file. According to the target project data, the preset generation rules are used to generate file tags corresponding to the target file, thereby realizing the classification management of the target files of the target project. In addition, the project files in the target project can be retrieved based on the file tags, so that file retrieval and file integration can be realized on the project intelligent management platform, thereby improving data processing efficiency and reducing the resource occupation of computing devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a schematic diagram of an application scenario of a data processing method provided by an embodiment of this specification; Figure 2 is a flow chart of a data processing method provided by an embodiment of this specification; Figure 3 is a processing flow chart of a data processing method provided by an embodiment of this specification; Figure 4 is a structural schematic diagram of a data processing device provided by an embodiment of this specification; Figure 5 It is a structural block diagram of a computing device provided by an embodiment of this specification. DETAILED DESCRIPTION

[0014] Many specific details are described in the following description to facilitate a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of this specification, so this specification is not limited to the specific implementation disclosed below.

[0015] The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of this specification. The singular forms of "a", "said" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0016] It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of this specification, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0017] In addition, it should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0018] In one or more embodiments of this specification, a large model refers to a deep learning model with large-scale model parameters, which usually contains hundreds of millions, tens of billions, hundreds of billions, trillions, or even more than 10 trillion model parameters. A large model can also be called a foundation model / foundation model. The large model is pre-trained with large-scale unlabeled corpus to produce a pre-trained model with more than 100 million parameters. This model can adapt to a wide range of downstream tasks, and the model has good generalization ability, such as a large-scale language model (LLM), a multi-modal pre-training model, etc.

[0019] When the big model is used in practice, only a small number of samples are needed to fine-tune the pre-trained model and it can be applied to different tasks. The big model can be widely used in natural language processing (NLP), computer vision and other fields. Specifically, it can be applied to computer vision tasks such as visual question answering (VQA), image caption (IC), image generation, as well as natural language processing tasks such as text-based sentiment classification, text summary generation, and machine translation. The main application scenarios of the big model include digital assistants, intelligent robots, search, online education, office software, e-commerce, intelligent design, etc.

[0020] First, the terms involved in one or more embodiments of this specification are explained.

[0021] API: Application Programming Interface, is a set of definitions, communication protocols and tools for building software and applications. It allows different software applications to interact with each other.

[0022] PDF: Portable Document Format, a file format.

[0023] Word: A file format.

[0024] Excel: A file format.

[0025] AI: Artificial Intelligence refers to intelligent behaviors exhibited by machines, including learning (obtaining information from data), reasoning (using rules to reach approximate or deterministic conclusions), and self-correction.

[0026] ETL (Extract, Transform, Load): The process of extracting, transforming, and loading data. This is an important part of the data warehouse, mainly used to extract data from different source systems, convert it into a consistent format, and load it into the target database or data warehouse.

[0027] TF-IDF: Term Frequency-Inverse Document Frequency, is a statistical method used to evaluate the importance of a word to a document or a set of documents in a corpus. TF stands for term frequency and IDF stands for inverse document frequency.

[0028] Word2Vec: is a model that maps words in a text into a vector space. These vectors capture the semantic relationship between words and can be used for various natural language processing tasks.

[0029] FastText: A library and techniques for efficiently learning word embeddings and n-grams that can be trained on large datasets in a short amount of time.

[0030] Bert: Bidirectional Encoder Representations from Transformers, a pre-trained natural language processing model based on the Transformer architecture. BERT can significantly improve the results of many NLP tasks by bidirectionally training each word in the text to understand the context.

[0031] In actual applications, in the current era of information explosion, professionals and enterprises are facing increasingly complex information management and efficient collaboration challenges. Although the market is flooded with a variety of tools and platforms, it has also spawned a series of new problems: information fragmentation, low retrieval efficiency, workflow fragmentation caused by multi-platform switching, and lack of personalized needs, all of which have a significant impact on daily affairs processing and team collaboration efficiency.

[0032] Specifically, the primary problem is the widespread dispersion of information. Key data such as key documents, communication records, and emails are scattered across multiple platforms, making the integration and retrieval process lengthy and cumbersome. Traditional search tools mostly rely on keyword matching and lack a deep understanding of user intent, resulting in inefficient information acquisition and even the possibility of missing important information. In addition, frequent multi-platform switching further exacerbates the complexity of the workflow and weakens overall work efficiency. More importantly, the current solutions on the market generally fail to fully consider user habits and contextual environments, and are unable to provide personalized recommendations that meet individual needs. Therefore, an effective technical solution is urgently needed to solve the above problems.

[0033] In this specification, a data processing method is provided. This specification also relates to a data processing device, a computing device, a computer-readable storage medium and a computer program product, which are described in detail one by one in the following embodiments.

[0034] See also Figure 1 , Figure 1 A schematic diagram of an application scenario of a data processing method provided according to an embodiment of the present specification is shown.

[0035] Figure 1 It includes a terminal device 102 and a project management intelligent platform 104.

[0036] In specific implementation, the project management intelligent platform 104 can be deployed on the terminal device 102, and the user can log in to the project management intelligent platform 104 through the terminal device 102 for project management. The project management intelligent platform 104 can respond to the file processing event of the target project, determine the target file of the target project, extract data from the target file, obtain the target project data recorded in the target file, generate a file tag corresponding to the target file according to the target project data and using preset generation rules, and manage and retrieve the target project according to the file tag.

[0037] The end-side device 102 may include a browser, an APP (Application), or a web application such as an H5 (Hyper Text Markup Language 5, version 5 of Hypertext Markup Language) application, or a light application (also known as a mini-program, a lightweight application) or a cloud application, etc. The end-side device may be based on a software development kit (SDK) of the corresponding service provided by the server, such as based on the real-time communication (RTC, Real Time Communication) SDK development and acquisition. The end-side device may be deployed in an electronic device and needs to rely on the device to run or some APPs in the device to run. The electronic device may have a display screen and support information browsing, such as a personal mobile terminal such as a mobile phone, a tablet computer, a personal computer, etc. Various other types of applications may also be configured in the electronic device, such as human-computer dialogue applications, model training applications, text processing applications, web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0038] See also Figure 2 , Figure 2 A flow chart of a data processing method provided according to an embodiment of the present specification is shown, which is applied to a project management intelligent platform and specifically includes the following steps.

[0039] Step 202: In response to a file processing event of a target project, determine a target file of the target project.

[0040] Among them, the project management intelligent platform can be understood as an intelligent platform for project management, and the project management intelligent platform can be deployed on the user's client. For example, for projects operated in an enterprise, the project management intelligent platform can be used to achieve the management and classification of project files in the project. The project management intelligent platform can manage multiple projects, and the target project can be understood as one of the multiple projects, and each project can include multiple project files. The target project can be understood as a project that needs to be managed. The file processing event of the target project can be understood as an event that creates or modifies a project file for the target project. The target file of the target project can be understood as a project file in the target project, created or modified. For example, a game development company develops a game project, then the target project can be a game project developed by the game development company, or, an e-commerce platform operates multiple shopping projects, then the target project can be a shopping project, and this specification embodiment does not limit this.

[0041] Specifically, in response to an event of creating or modifying a project file for a target project, a project file created or modified in the target project may be determined as the target file.

[0042] For example, the project management intelligent platform is used to manage multiple game projects developed by a certain enterprise. For one of the game projects, in response to an event of creating or modifying a project file for the game project, the project file 1 created or modified in the game project can be determined as the target file.

[0043] In actual applications, when the project management intelligent platform is started, it can be based on the update detection mechanism to synchronously detect whether there is an updated version. Specifically, it can automatically scan the preset update source, including but not limited to local storage, LAN shared resources and external storage devices, etc., and can also set up a scheduled task to check whether there is an updated version every day to ensure that the project management intelligent platform is continuously in the latest state. If there is an updated version, before the update, the core data and configuration files of the current version can be backed up. In the update execution process, file replacement and configuration and dependency synchronization can be performed. Specifically, the updated file can replace the file before the update to ensure the complete application of the updated content. With the version change, the relevant configuration and dependencies can be automatically adjusted. For example, if it involves changes in the database structure, the corresponding data migration script can be executed to ensure data consistency. After completing all the update steps, you can enter the restart verification process to automatically restart the project management intelligent platform to load and verify the normal operation of the new version. After the new version is started, you can perform a self-check process to ensure that the operation is stable and then notify the user that the update is successful. If an abnormality is found during the self-check process, it can automatically roll back to the old version that was backed up and notify the user of the relevant situation.

[0044] In addition, in actual applications, when the project management intelligent platform is started, it can automatically start and continuously provide background service support, create and run the system tray icon, and provide users with a convenient interactive interface through the right-click menu to further enhance the user experience. You can use the API provided by the operating system to register global shortcut keys. When it is detected that the global shortcut key is pressed, you can perform corresponding operations, such as showing or hiding the application panel. The registration and event processing logic of the global shortcut key can be integrated in the tray application to achieve unified management, ensure the seamless integration of the shortcut key function with the system tray application, and enable users to quickly call functions through shortcut keys to optimize the user experience.

[0045] In a specific implementation, the step of determining the target file of the target project in response to the file processing event of the target project includes: Scanning the target storage location corresponding to the target item according to a preset time interval to obtain a scanning result; In a case where it is determined according to the scanning result that there is a file processing event of the target project, a target file of the target project is determined.

[0046] The preset time interval can be understood as the scanning time interval for the target project, for example, the preset time interval can be every hour or every day, and the preset time interval can be determined according to project requirements and server performance. The target storage location corresponding to the target project can be understood as the location where the project files of the target project are stored, for example, the folder and file type where the project files of the target project are stored.

[0047] Specifically, the location where the project file of the target project is stored can be scanned according to the scanning time interval for the target project to obtain the scanning result. If it is determined according to the scanning result that there is an event of creating or modifying the project file of the target project, the created or modified project file in the target project is determined as the target file.

[0048] In actual applications, the project management intelligent platform can establish a file listener, using the file system monitoring API provided by the client's operating system, and the user can specify the folders and file types (such as documents, emails, contacts, etc.) to be monitored, set trigger events, and trigger when a file creation event, file modification event, or file deletion event is monitored. In addition, the scanning frequency (i.e., the preset time interval) can be set, and the entire file system in the client is scanned regularly according to the scanning frequency to ensure that no file changes are missed.

[0049] In summary, by performing file monitoring and full disk scanning, the triggering of file processing events can be achieved, thereby avoiding missing file changes and further improving file management efficiency.

[0050] Step 204: extract data from the target file to obtain target project data recorded in the target file.

[0051] Specifically, after the newly added or modified project file (ie, the target file) is captured, data extraction (ie, text content extraction) may be performed on the target file to obtain the target project data recorded in the target file.

[0052] In actual applications, when extracting data from a target file, the content of the target file in various file formats may be parsed, including but not limited to PDF, Word, and Excel.

[0053] In a specific implementation, extracting data from the target file to obtain the target project data recorded in the target file includes: Extracting data from the target file to obtain text content recorded in the target file and metadata of the target file; The text content and the metadata are determined as target item data recorded in the target file.

[0054] The metadata of the target file may include but is not limited to the creator and creation time of the target file.

[0055] Specifically, data may be extracted from the target file to obtain text content and metadata of the target file, and the text content and metadata may be determined as target item data recorded in the target file.

[0056] In practical applications, data extraction can be performed using a language processing model or a large model, and the embodiments of this specification do not limit this.

[0057] In summary, by extracting data from the target file, it is convenient to subsequently generate a file label for the target file, making the generated file label more accurate.

[0058] Step 206: Generate a file tag corresponding to the target file according to the target project data using a preset generation rule, so as to search the target project according to the file tag.

[0059] The preset generation rule can be understood as a pre-created rule for generating file tags. The file tag can be understood as a classification tag of the target file, such as the content type of the target file, the subject type of the target file, the project type of the target file, etc.

[0060] In actual applications, a set of rules can be created in advance to cover different content types, topics, projects, etc. The preset generation rules can be created based on keywords, regular expressions, and file attributes. Based on this, the target project data of the captured target file can be matched according to the preset generation rules, and the corresponding file tags can be automatically applied.

[0061] In one embodiment of the present specification, generating a file tag corresponding to the target file according to the target project data using a preset generation rule includes: Matching the target project data with the preset generation rule to obtain a matching result; According to the matching result, a file tag corresponding to the target file is determined.

[0062] Specifically, the preset generation rule may be, for example, "Define the file tag of the project file that meets the preset condition as A", then the target project data and the preset generation rule may be matched to obtain a matching result, and when it is determined according to the matching result that the target project data meets the preset condition, the file tag corresponding to the target file is determined to be A. The target project data meeting the preset condition may be, for example, that the target project data contains chat records of two people, then the file tag may be "chat records".

[0063] In another embodiment of the present specification, generating a file tag corresponding to the target file according to the target project data using a preset generation rule includes: Using a preset generation rule, extracting keywords corresponding to the preset generation rule from the target project data; The keyword is determined as a file tag corresponding to the target file.

[0064] Specifically, the preset generation rule may be a rule based on keywords, for example. Then, the preset generation rule may be used to extract keywords from the target project data, and the keywords are determined as the file tags corresponding to the target file. For example, the keyword that can be extracted from the target project data is "email", and the keyword is determined as the file tag of the target file. Alternatively, the preset generation rule may be a rule based on file attributes, and the preset generation rule may be used to extract file attribute information from the target project data, and the file attribute information is determined as the file tag corresponding to the target file. For example, the file attribute information that can be extracted from the target project data is "creator A", and the file attribute information is determined as the file tag of the target file.

[0065] In addition, when the target file matches multiple preset generation rules, for example, for the target file, the extracted keyword is "email", and the file attribute information is "creator A" and "creation time period 2024.10.13", then the final file label can be determined from the multiple labels according to the label priority strategy or other comprehensive strategies. For example, the pre-created label priority strategy is that the file creation time has the highest priority, so the final file label determined is "creation time period 2024.10.13". In actual applications, the project information of the target project can also be obtained from the project management software, the file content of the target file is matched, the matching result is obtained, and the file label is automatically generated according to the matching result.

[0066] Furthermore, in another embodiment of the present specification, after obtaining the target project data recorded in the target file, the method further includes: The target project data is processed using a label generation model to obtain a file label corresponding to the target file.

[0067] Among them, the label generation model can be understood as a model used to classify and label the target files, for example, it can be a pre-trained model (such as the Bert model).

[0068] In practical applications, natural language processing tools can be used to analyze the target project data of the target file and automatically generate file tags for the target file.

[0069] In summary, by utilizing the label generation model, the file label generation of the target file is achieved.

[0070] In practical applications, the tag generation model is used to process the target project data to obtain the file tag corresponding to the target file, and the following is also included: Preprocessing the target project data to obtain preprocessed target project data; Performing text processing on the preprocessed target project data to obtain keywords and semantic information of the target project data; The using of the label generation model to process the target project data to obtain a file label corresponding to the target file includes: The keyword and semantic information are processed using a tag generation model to obtain a file tag corresponding to the target file.

[0071] Specifically, when preprocessing the target project data, the target project data can be cleaned, segmented and annotated to obtain the preprocessed target project data, and key features can be extracted from the preprocessed target project data to obtain keywords and semantic information of the target project data. Based on the keywords and semantic information, a label generation model is used to classify the target files and generate file labels for the target files.

[0072] In practical applications, the target project data is text data, and the target project data can be cleaned up. For example, stop words and punctuation marks in the target project data can be removed, stem extraction and word form restoration can be performed, and word segmentation and part-of-speech tagging can be performed on the target project data. Key feature words (i.e., keywords) in the target project data can be extracted using methods such as TF-IDF and word frequency statistics. A language processing model (such as Word2Vec or FastText, etc.) can be used to generate a contextual representation of the target project data. The contextual representation is determined as the semantic information of the target project data. Based on the key feature words and semantic information, a label generation model can be used to classify the target file and generate a file label for the target file.

[0073] In addition, the label generation model can be regularly trained and updated to adapt to user label usage habits and improve the accuracy of label generation and recommendation. Specifically, the label generation model can be dynamically adjusted according to the file labels manually adjusted by the user, and user behavior data (such as label addition, deletion, modification, etc.) can be collected to continuously optimize the label generation model and achieve continuous optimization of the recommendation algorithm.

[0074] In summary, by automatically generating recommended tags and regularly training the tag generation model, the accuracy of the generated file tags is achieved, and the tag generation model is adapted to and improves the recognition accuracy of user tag usage habits. With the help of advanced natural language processing technology, it can deeply understand user intentions, support fuzzy search and complex query requirements, and thus significantly improve the accuracy and efficiency of information retrieval.

[0075] In practical applications, the file tag corresponding to the target file is generated according to the target project data using a preset generation rule, including: According to the target project data, using the preset generation rule, generating a plurality of file tags corresponding to the target file; After generating a plurality of file tags corresponding to the target file, the method further includes: The plurality of file tags are stored in a hierarchical structure.

[0076] The types of the multiple file tags may be different, and the multiple file tags may include, for example, category tags, project tags, time period tags, etc.

[0077] Specifically, based on the target project data, a plurality of file tags corresponding to the target file may be generated by using preset generation rules, and a tag database may be created and maintained, in which the plurality of file tags may be stored in a hierarchical structure.

[0078] In practical applications, a tag database can be built and tags can be organized in a hierarchical structure (such as category > project > time period) to ensure the systematic and searchable nature of file management.

[0079] Further, storing the plurality of file tags in a hierarchical structure includes: storing the plurality of file tags in a cloud database in a hierarchical structure; The method further comprises: The target file of the target project is stored in a local database.

[0080] The cloud database can be understood as a database deployed in the cloud, and the local database can be understood as a database deployed locally on the client.

[0081] Specifically, multiple file tags may be stored in a cloud database in a hierarchical structure, and the target file of the target project may be stored in a local database of the client.

[0082] In summary, by storing file tags in the cloud database, it is convenient for the server to update tag information, and at the same time it is convenient for model learning, so as to achieve the reusability of file tags and facilitate the same-authority personnel in the project team to obtain and use file tags from the cloud database, realize collaborative sharing of file tags, and store the target files in the client's local database to ensure the security of project data.

[0083] In practical applications, in another embodiment of this specification, all data (project files, file tags, user preferences, user behavior data, etc.) can also be stored in the local storage medium of the client to avoid cloud dependence, and local database technology can be used to achieve efficient structured storage and management of data, which is not limited in this embodiment of this specification. In addition, the project management intelligent platform can realize offline operation, and all processing and computing tasks can be completed independently on local devices (such as local clients) to avoid network dependence. The project management intelligent platform can also provide offline access and operation functions to ensure the normal user experience in a network-free environment.

[0084] In addition, the project management intelligent platform can also set differentiated access rights for file tags and their associated content to ensure the security of sensitive information, implement role-based access control, and clearly define the scope of permissions for different user groups. Specifically, when the target user searches for the target project, the project management intelligent platform can determine whether the target user has access rights to the target project. If so, the target user is allowed to access the target project. If not, the target user is not allowed to access the target project. It effectively protects the privacy and security of data, and is supplemented by a fine-grained permission control mechanism to prevent unauthorized access to sensitive information.

[0085] In one embodiment of the present specification, the target user can also customize the tag management and whitelist services in the project management intelligent platform, and the target user can create, edit, delete and adjust the hierarchical structure of the customized tags through drag and drop operations. In addition, the target user can customize the whitelist to exclude data records of specific programs or storage paths, provide a convenient whitelist management interface, and simplify the operation process of adding and removing entries.

[0086] In one embodiment of the present specification, sensitive data can be identified in all project files included in the target project, and the sensitive data can be encrypted and stored to ensure data security. In addition, a permission control system can be established to limit the access rights of unauthorized users and applications.

[0087] In one embodiment of the present specification, a data backup tool may be used to back up all project data of a target project to an external storage device, and a data backup reminder may be sent to the user regularly to remind the user to back up data in time to prevent accidental loss.

[0088] In one embodiment of the present specification, the project management intelligent platform may not rely on any form of cloud storage or cloud computing services, and all data processing and computing tasks are completed based on local hardware resources to avoid dependence on cloud services.

[0089] In one embodiment of the present specification, the target user can transfer project data of the target project between different devices based on the data import and export function provided by the project management intelligent platform, thereby realizing data collaboration and sharing, and the data format of the exported project data is easy to transplant and reuse.

[0090] In one embodiment of the present specification, when the target user starts to use the project management intelligent platform, a privacy statement can be issued to the target user, clearly disclosing to the target user that the project data is only stored on the local device, formulating and issuing a clear and understandable privacy statement, and enhancing the user's trust in data protection measures.

[0091] Specifically, searching the target item according to the file tag includes: Receiving a file search instruction from a target user, wherein the file search instruction carries a search keyword; Determine the search file corresponding to the file search instruction according to the search keyword and the file tags of the plurality of target files in the target project; The file storage path of the searched file is displayed so that the target user can obtain the searched file according to the file storage path.

[0092] The file search instruction may be understood as a file search instruction initiated by the target user through the client, and the search keyword carried in the file search instruction may be a keyword input by the target user through the client. The file storage path may be understood as a storage location where the searched file is stored.

[0093] Specifically, the project management intelligent platform is deployed on the client of the target user. The target user can log in to the project management intelligent platform through the client, enter the search keyword in the search engine of the project management intelligent platform, and generate a file retrieval instruction by clicking the "Search" control on the display interface. The project management intelligent platform receives the file retrieval instruction carrying the search keyword, and determines the target file tag corresponding to the search keyword based on the search keyword and the file tags of multiple target files in the target project, thereby determining the retrieval file corresponding to the target file tag, and uses the retrieval file as the retrieval file corresponding to the file retrieval instruction, and displays the file storage path of the retrieval file on the display interface of the project management intelligent platform, so that the target user can obtain the retrieval file according to the file storage path.

[0094] In addition, there may be multiple retrieval files corresponding to the determined file retrieval instruction, so the file storage paths of the multiple retrieval files may be displayed for the user to select.

[0095] In actual applications, this project management intelligent platform can integrate search engines based on keyword matching technology to achieve full-text retrieval capabilities. The tag field of the file tag is included when building the retrieval index, thereby accelerating the tag matching speed during the retrieval process. When presenting the retrieval results, the retrieval results can be displayed on the user interface. The retrieval results can include multiple matching file tags and file storage paths. A variety of sorting options can be provided (such as sorting by relevance and sorting by time, etc.), and the retrieved multiple file tags and file storage paths can be sorted according to a variety of sorting options to meet the diverse needs of users. When displaying the retrieval results, not only the file tags are displayed, but also the complete file storage path. The file storage path can be displayed in the form of a clickable link, which is convenient for the target user to jump directly to the target file storage location by clicking the link.

[0096] In addition, you can also use the API provided by the operating system to create shortcuts to quickly launch related applications. When the user clicks on the search results, you can achieve path navigation and direct opening of files or applications, and realize one-click application awakening. The project management intelligent platform can display an intuitive and easy-to-use user interface, display the retrieved file tags and file storage paths, and integrate a filtering function that allows users to further filter search results based on file tags, file storage paths, file keywords and other conditions.

[0097] In the process of displaying the integrated content date for the target project, the target file contained in the target project is taken as a conference file as an example. The target user can enter a search message, and can use the file tags corresponding to each project file in the target project to perform information retrieval. Through natural language processing technology, the content of the search message is extracted, and it is determined whether the search message contains specific keywords closely related to the conference content. In addition, for the target user performing the search, the user identifier of the target user can be matched, and the user identity of the target user can be verified to confirm whether the search message clearly points to a specific user. Specifically, the user information mentioned in the search message (such as name, nickname or common pronouns) can be detected. Date and time information can also be extracted. Natural language processing tools can be used to accurately identify and extract the date and time information contained in the search message, and the extracted date and time information can be converted into a standardized format for subsequent data processing and intuitive display. According to the extracted date and time information, the response message corresponding to the search message is edited to facilitate users to quickly obtain the required information, and the response message is presented to the target user through the application interface.

[0098] In summary, by displaying an intuitive and easy-to-use user interface, it can summarize project information and task progress, helping users to obtain the required data with one click; for improving personal productivity, it can quickly retrieve and present the files and information required for daily work, and provide intelligent reminder services to help users optimize their schedules. In the field of customer service and support, it can integrate customer communication records to achieve rapid response and problem solving, and automatically update at the same time.

[0099] In addition, the data processing method also includes: A target project report corresponding to the target project is generated according to a plurality of target files included in the target project and the file processing time of the plurality of target files.

[0100] The target file processing time may be understood as the time when the target file is created or modified. The target project report may be a project progress report of the target project.

[0101] Specifically, a target project report corresponding to the target project may be generated according to all project files included in the target project and the file processing time of each project file.

[0102] In practical applications, the tag database (i.e., tag system) created above can be used to perform data collection tasks for target projects. Specifically, the pre-trained machine learning model can be used to comprehensively clean the collected data of the target project, remove duplicate data and irrelevant data, and convert data from different channels into a unified format to ensure the standardization of the data and the convenience of subsequent processing. Based on natural language processing technology, keyword texts closely related to the project progress can be automatically identified and annotated, and the communication content contained in the data can be analyzed to evaluate its emotional state, thereby evaluating the overall health of the target project, and the entity information such as tasks, dates, and personnel involved in the data can be extracted. Cloud databases can be used as data storage and management platforms to ensure data security and accessibility, realize the automated execution of ETL (Extract, Transform, Load) processes, and efficiently complete data extraction, transformation, and loading tasks. Timestamps are added to all data records in the target project, so that the file processing time of each project file in the target project can be obtained, providing a solid foundation for time series analysis and progress tracking of the target project. Data statistical methods and machine learning algorithms can be used to predict the changing trend of the progress of the target project and provide support for subsequent decision-making on the target project. Dynamic data visualization tools can be used to intuitively display the progress of the target project. Interactive charts (such as Gantt charts, progress bars, timelines, and other chart forms) can be used to display the current status and progress of the target project. Based on natural language generation technology, a project progress report for the target project is generated and sent to relevant personnel through multiple channels such as email, instant messaging, or in-app notifications.

[0103] In summary, the project management intelligent platform can be understood as an AI collaborative assistant deployed on the user client. The AI ​​collaborative assistant integrates multi-platform data sources and realizes centralized information processing through a unified search interface, effectively avoiding the decentralized state of information. With the help of advanced natural language processing technology, the assistant can deeply understand user intentions, support fuzzy searches and complex query requirements, thereby significantly improving the accuracy and efficiency of information retrieval. In addition, the assistant also has an intelligent recommendation function, which automatically recommends relevant files, contacts, and information resources based on user behavior and contextual information, bringing great convenience to users' work.

[0104] In terms of real-time collaboration and sharing, the AI ​​collaboration assistant breaks the boundaries between teams and platforms, supports real-time document sharing and editing across teams and platforms, and is equipped with version control and change tracking functions to ensure the consistency and traceability of information. From the perspective of security and privacy protection, the assistant is based on a local storage model, effectively protecting the privacy and security of data, and is supplemented by a fine-grained permission control mechanism to prevent unauthorized access to sensitive information.

[0105] Personalized assistant service is another major feature of AI collaborative assistant. This service customizes the interface and function modules according to the user's personal preferences and historical records, and integrates the shortcut key pull-up method to further enhance the user's interactive experience. This innovative design not only optimizes the user experience, but also significantly enhances the user's dependence on and satisfaction with the tool.

[0106] In terms of application scenarios, the AI ​​collaboration assistant has demonstrated a wide range of adaptability. In the field of internal enterprise collaboration, the assistant can be applied to project management, easily summarizing project information and task progress, and helping users obtain the required data with one click; for improving personal productivity, the AI ​​collaboration assistant can quickly retrieve and present the files and information required for daily work, while providing intelligent reminder services to help users optimize their schedules. In the field of customer service and support, the assistant can integrate customer communication records, achieve rapid response and problem solving, and automatically update.

[0107] The following combination Figure 3 , taking the application of the data processing method provided in this specification in project management as an example, the data processing method is further explained. Figure 3 A processing flow chart of a data processing method provided by an embodiment of the present specification is shown, which specifically includes the following steps.

[0108] Step 302: The project management intelligent platform is started.

[0109] Step 304: Update check.

[0110] Step 306: When it is determined that there is an updated version, the current version is backed up and updated.

[0111] Step 308: Determine whether the update is successful, if so, restart, if not, roll back.

[0112] Step 310: Start the background service.

[0113] Step 312: Continue monitoring.

[0114] Step 314: Scan.

[0115] When a file processing event of a target project is detected, a target file of the target project is determined, and a file tag is created for the target file.

[0116] Step 316: If the file tag is a new tag, then create the file tag; if the file tag is not a new tag, it means that the target file already has a file tag, then update the existing file tag.

[0117] Step 318: Store the created or updated file tag in the local database. Step 320: Store the created or updated file tag in the cloud database.

[0118] Step 322: Detect the shortcut key.

[0119] Step 324: Invoke the user panel.

[0120] Step 326: Generate a target project report for the target project.

[0121] Step 328: Detect a retrieval instruction.

[0122] Step 330: Network detection.

[0123] Specifically, a network detection may be performed, and when it is determined that the current network connection status is normal, the file tag is obtained from the cloud database; when it is determined that the current network connection status is abnormal (for example, the network connection is disconnected), the file tag is directly obtained from the local database.

[0124] Step 332: Matching data.

[0125] Match the search keywords carried in the search instruction with the obtained file tags to obtain the search results. If the match fails, the process ends.

[0126] Step 334: Obtain and display the search results.

[0127] If the search results contain options, you can call up an application or path based on the options. If not, the process ends.

[0128] Corresponding to the above method embodiment, this specification also provides a data processing device embodiment, Figure 4 FIG. 1 is a schematic diagram showing the structure of a data processing device provided by an embodiment of the present specification. Figure 4 As shown, the device comprises: A determination module 402 is configured to determine a target file of the target project in response to a file processing event of the target project; The extraction module 404 is configured to extract data from the target file to obtain the target project data recorded in the target file; The generation module 406 is configured to generate a file tag corresponding to the target file according to the target project data and using a preset generation rule, so as to search the target project according to the file tag.

[0129] The determination module 402 is configured to: Scanning the target storage location corresponding to the target item according to a preset time interval to obtain a scanning result; In a case where it is determined according to the scanning result that there is a file processing event of the target project, a target file of the target project is determined.

[0130] In an optional embodiment, the extraction module 404 is further configured to: Extracting data from the target file to obtain text content recorded in the target file and metadata of the target file; The text content and the metadata are determined as target item data recorded in the target file.

[0131] In an optional embodiment, the generating module 406 is further configured to: Matching the target project data with the preset generation rule to obtain a matching result; According to the matching result, a file tag corresponding to the target file is determined.

[0132] In an optional embodiment, the generating module 406 is further configured to: Using a preset generation rule, extracting keywords corresponding to the preset generation rule from the target project data; The keyword is determined as a file tag corresponding to the target file.

[0133] In an optional embodiment, the generating module 406 is further configured to: The target project data is processed using a label generation model to obtain a file label corresponding to the target file.

[0134] In an optional embodiment, the generating module 406 is further configured to: Preprocessing the target project data to obtain preprocessed target project data; Performing text processing on the preprocessed target project data to obtain keywords and semantic information of the target project data; The keyword and semantic information are processed using a tag generation model to obtain a file tag corresponding to the target file.

[0135] In an optional embodiment, the generating module 406 is further configured to: According to the target project data, using the preset generation rule, generating a plurality of file tags corresponding to the target file; The plurality of file tags are stored in a hierarchical structure.

[0136] In an optional embodiment, the generating module 406 is further configured to: storing the plurality of file tags in a cloud database in a hierarchical structure; The target file of the target project is stored in a local database.

[0137] In an optional embodiment, the determining module 402 is further configured to: A target project report corresponding to the target project is generated according to a plurality of target files included in the target project and the file processing time of the plurality of target files.

[0138] In an optional embodiment, the device further includes a retrieval module configured to: Receiving a file search instruction from a target user, wherein the file search instruction carries a search keyword; Determine the search file corresponding to the file search instruction according to the search keyword and the file tags of the plurality of target files in the target project; The file storage path of the searched file is displayed so that the target user can obtain the searched file according to the file storage path.

[0139] The above is a schematic scheme of a data processing device of this embodiment. It should be noted that the technical scheme of the data processing device and the technical scheme of the above data processing method belong to the same concept, and the details of the technical scheme of the data processing device that are not described in detail can be referred to the description of the technical scheme of the above data processing method.

[0140] Corresponding to the above method embodiment, the embodiment of this specification also provides another data processing method, which specifically includes the following steps.

[0141] Receiving a file search instruction for a target project from a target user, wherein the file search instruction carries a search keyword; Determine the retrieval file corresponding to the file retrieval instruction according to the retrieval keyword and the file tags of the multiple target files in the target project, wherein the file tags of the multiple target files in the target project are determined according to the method provided in the first aspect of the embodiment of this specification; The retrieved file is displayed to the target user.

[0142] Specifically, the data processing method can be applied to a project management intelligent platform. The project management intelligent platform can be deployed on a client, and after receiving a file search instruction for a target project from a target user, the search file corresponding to the file search instruction is determined according to the search keywords carried in the file search instruction and the file tags of multiple target files in the target project, and the search file is displayed to the target user to realize file search.

[0143] Corresponding to the above method embodiment, the embodiment of this specification also provides a data processing device, including: A receiving module is configured to receive a file search instruction from a target user for a target project, wherein the file search instruction carries a search keyword; a determination module configured to determine the retrieval file corresponding to the file retrieval instruction according to the retrieval keyword and the file tags of the multiple target files in the target project, wherein the file tags of the multiple target files in the target project are determined according to the method provided in the first aspect of the embodiment of this specification; A display module is configured to display the retrieved file to the target user.

[0144] The above is a schematic scheme of a data processing device of this embodiment. It should be noted that the technical scheme of the data processing device and the technical scheme of the above data processing method belong to the same concept, and the details of the technical scheme of the data processing device that are not described in detail can be referred to the description of the technical scheme of the above data processing method.

[0145] Figure 5 The structure block diagram of a computing device 500 provided according to an embodiment of the present specification is shown. The components of the computing device 500 include but are not limited to a memory 510 and a processor 520. The processor 520 is connected to the memory 510 via a bus 530, and the database 550 is used to store data.

[0146] The computing device 500 also includes an access device 540 that enables the computing device 500 to communicate via one or more networks 560. Examples of these networks include a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a combination of communication networks such as the Internet. The access device 540 may include one or more of any type of network interface (e.g., a network interface card (NIC)) that is wired or wireless, such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a world-wide interoperability for microwave access (Wi-MAX) interface, an Ethernet interface, a universal serial bus (USB) interface, a cellular network interface, a Bluetooth interface, and a near field communication (NFC).

[0147] In one embodiment of the present specification, the above components of the computing device 500 and Figure 5 Other components not shown in the figure may also be connected to each other, for example, via a bus. It should be understood that Figure 5 The computing device structure block diagram shown is only for the purpose of illustration, and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0148] The computing device 500 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.), or other types of mobile devices, or a stationary computing device such as a desktop computer or a personal computer (PC). The computing device 500 may also be a mobile or stationary server.

[0149] The processor 520 is used to execute the following computer program / instructions, which implement the steps of the above method when executed by the processor.

[0150] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the computing device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0151] An embodiment of the present specification further provides a computer-readable storage medium storing a computer program / instruction, which implements the steps of the above method when executed by a processor.

[0152] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the computer-readable storage medium embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0153] An embodiment of the present specification also provides a computer program product, including a computer program / instruction, which implements the steps of the above method when executed by a processor.

[0154] The above is a schematic solution of a computer program product of this embodiment. It should be noted that the technical solution of the computer program product and the technical solution of the above method belong to the same concept, and the details not described in detail in the technical solution of the computer program product can be referred to the description of the technical solution of the above method.

[0155] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0156] The computer instructions include computer program codes, which may be in source code form, object code form, executable files or some intermediate forms, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of patent practice. For example, in some regions, according to patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0157] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of this specification are not limited by the order of the actions described, because according to the embodiments of this specification, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of this specification.

[0158] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0159] The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that technicians in the relevant technical field can well understand and use this specification. This specification is only limited by the claims and their full scope and equivalents.

Claims

1. A data processing method, applied to a project management intelligent platform, characterized in that: include: In response to a file processing event of a target project, determining a target file of the target project; Extracting data from the target file to obtain target project data recorded in the target file; According to the target project data, a file tag corresponding to the target file is generated using a preset generation rule, so as to retrieve the target project according to the file tag.

2. The method according to claim 1, characterized in that The step of determining the target file of the target project in response to the file processing event of the target project comprises: Scanning the target storage location corresponding to the target item according to a preset time interval to obtain a scanning result; In a case where it is determined according to the scanning result that there is a file processing event of the target project, a target file of the target project is determined.

3. The method according to claim 1, characterized in that The step of extracting data from the target file to obtain target project data recorded in the target file includes: Extracting data from the target file to obtain text content recorded in the target file and metadata of the target file; The text content and the metadata are determined as target item data recorded in the target file.

4. The method according to any one of claims 1 to 3, characterized in that: The step of generating a file tag corresponding to the target file according to the target project data and using a preset generation rule includes: Matching the target project data with the preset generation rule to obtain a matching result; According to the matching result, a file tag corresponding to the target file is determined.

5. The method according to any one of claims 1 to 3, characterized in that: The step of generating a file tag corresponding to the target file according to the target project data and using a preset generation rule includes: Using a preset generation rule, extracting keywords corresponding to the preset generation rule from the target project data; The keyword is determined as a file tag corresponding to the target file.

6. The method according to any one of claims 1 to 3, characterized in that: After obtaining the target project data recorded in the target file, the method further includes: The target project data is processed using a label generation model to obtain a file label corresponding to the target file.

7. The method according to claim 6, characterized in that Before the target project data is processed by using the label generation model to obtain the file label corresponding to the target file, the method further includes: Preprocessing the target project data to obtain preprocessed target project data; Performing text processing on the preprocessed target project data to obtain keywords and semantic information of the target project data; The using of the label generation model to process the target project data to obtain a file label corresponding to the target file includes: The keyword and semantic information are processed using a tag generation model to obtain a file tag corresponding to the target file.

8. The method according to any one of claims 1 to 3, characterized in that: The step of generating a file tag corresponding to the target file according to the target project data and using a preset generation rule includes: According to the target project data, using the preset generation rule, generating a plurality of file tags corresponding to the target file; After generating a plurality of file tags corresponding to the target file, the method further includes: The plurality of file tags are stored in a hierarchical structure.

9. The method according to claim 8, characterized in that The storing the plurality of file tags in a hierarchical structure comprises: storing the plurality of file tags in a cloud database in a hierarchical structure; The method further comprises: The target file of the target project is stored in a local database.

10. The method according to any one of claims 1 to 3, characterized in that: Also includes: A target project report corresponding to the target project is generated according to a plurality of target files included in the target project and the file processing time of the plurality of target files.

11. The method according to any one of claims 1 to 3, characterized in that: The retrieving the target item according to the file tag includes: Receiving a file search instruction from a target user, wherein the file search instruction carries a search keyword; Determine the search file corresponding to the file search instruction according to the search keyword and the file tags of the plurality of target files in the target project; The file storage path of the searched file is displayed so that the target user can obtain the searched file according to the file storage path.

12. A data processing method, characterized in that: include: Receiving a file search instruction for a target project from a target user, wherein the file search instruction carries a search keyword; Determining the retrieval file corresponding to the file retrieval instruction according to the retrieval keyword and the file tags of the multiple target files in the target project, wherein the file tags of the multiple target files in the target project are determined according to the method according to any one of claims 1 to 10; The retrieved file is displayed to the target user.

13. A computing device, characterized in that: include: Memory and processor; The memory is used to store computer programs / instructions, and the processor is used to execute the computer programs / instructions. When the computer programs / instructions are executed by the processor, the steps of the method described in any one of claims 1 to 12 are implemented.

14. A computer-readable storage medium, characterized in that: It stores a computer program / instruction, which, when executed by a processor, implements the steps of the method described in any one of claims 1 to 12.

15. A computer program product, characterized in that The invention comprises a computer program / instruction, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 12.

Images